At a Glance
- Tasks: Design and deliver cutting-edge AWS data architectures for high-profile projects.
- Company: Leading consultancy with a focus on technology and innovation.
- Benefits: Up to £95,000 salary, comprehensive benefits, and hybrid working model.
- Other info: Opportunities for continuous learning and clear career progression.
- Why this job: Shape enterprise data strategies and work on transformative cloud-native solutions.
- Qualifications: Experience in data architecture and strong AWS expertise required.
The predicted salary is between 70000 - 90000 £ per year.
A leading consultancy is seeking an experienced AWS Data Architect to join its growing Technology Consulting practice. This is an opportunity to work on high-profile projects across regulated and public sector environments, shaping enterprise data strategies and delivering cutting-edge cloud-native solutions.
The Role
As a Data Architect, you will be responsible for defining architecture strategy, providing technical leadership and guiding the delivery of scalable data, analytics and AI platforms. Working closely with senior client stakeholders, engineering teams and business leaders, you will help organisations unlock value from their data while ensuring solutions are secure, resilient and future‑ready.
Responsibilities
- Designing enterprise‑scale AWS data and analytics architectures
- Leading the delivery of cloud‑native data platforms across the full data lifecycle
- Integrating machine learning, Generative AI and large language model capabilities into business solutions
- Defining data governance, security and architecture standards
- Advising senior stakeholders on technology strategy and roadmap development
- Leading and mentoring multidisciplinary teams of architects and engineers
About You
- Experience in data, analytics or AI architecture
- Strong expertise across AWS data and analytics services
- Experience designing both batch and real‑time data processing solutions
- Knowledge of modern cloud architecture patterns including APIs and microservices
- Experience implementing machine learning, Generative AI and AI‑enabled solutions
- Strong understanding of data governance, security and compliance requirements
- Excellent communication and leadership skills
What’s on Offer
- Salary up to £95,000
- Comprehensive benefits package
- Hybrid working model
- Continuous learning and career development opportunities
- Exposure to large‑scale cloud, data and AI transformation programmes
- Opportunity to work alongside highly experienced consultants and architects
- Clear progression path within a growing consultancy environment
AWS Data Architect in Manchester employer: Nigel Frank
Join a forward-thinking organisation that prioritises innovation and collaboration, offering a dynamic work environment for a Senior Power Platform Developer. With a strong focus on employee growth, you will have the opportunity to lead projects, mentor fellow developers, and shape the technical direction of the company while enjoying the flexibility of a hybrid working model. This role not only provides competitive remuneration but also fosters a culture of continuous learning and development, making it an excellent choice for those seeking meaningful and rewarding employment in the tech industry.
StudySmarter Expert Advice🤫
We think this is how you could land AWS Data Architect in Manchester
✨Get Involved in Data Science Meetups
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We think you need these skills to ace AWS Data Architect in Manchester
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Nigel Frank, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Nigel Frank. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Nigel Frank
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Nigel Frank!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
